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INDIAN JOURNAL

OF

CRIMINOLOGY

Volume 46 & 47

2018-19

INDIAN JOURNAL OF CRIMINOLOGY

The Indian Journal of Criminology is a joint publication of Indian Society of Criminology (ISC), K.L.

Arora Chair in Criminal Law and Centre for Criminology and Victimology at National Law University

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Panakal, J.J. (1973). An Agenda for Criminology

Indian Journal of Criminology, 1(1). 1-5.

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The Indian Journal of Criminology

Editor:

Prof. (Dr.) G. S. Bajpai

Professor of Criminology & Criminal Justice, NLU Delhi India

Managing Editor:

Dr. Syed Umarhathab

Assistant Professor, M.S. University, Tirunelveli, India

Executive Editors:

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Associate Professor, NLU Delhi

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Assistant Librarian, NLU Delhi

Dr. Garima Pal

Research Associate,NLU Delhi

Editorial & Advisory Board

Prof. Ian Loader

Professor of Criminology

University of Oxford, UK

Prof. Zbigniew Lasocik

Professor of Legal Sciences and Criminology

University of Warsaw, Poland

Prof. N. Prabha Unnithan

Director, Centre for the Study of Crime and

Justice

Department of Sociology, Colorado State

University

Prof. K. Jaishankar

Professor and Head Department of Criminology

Raksha Shakti University, Ahmedabad, India

Prof. (Dr.) Purvi Pokhariyal

Director & Dean, Institute of Law

Nirma University, Ahmedabad, India

Dr. Suman Dash Bhattamishra

Assistant Professor of Law

National Law University, Odisha

Mr. Emilio C. Viano

President

International Society of Criminology, USA

Prof. Jianhong Liu

University of Macau, Macau, China

Dr. G. K. Goswami, IPS

Joint Director

Anti-Corruption Zone, C.B.I. New Delhi

Prof. Arvind Tiwari

Dean, School of Law, Rights and Constitutional

Governance

Tata Institute of Sciences, Mumbai, India

Prof. (Dr.) P. Madhava Soma Sundaram

M.S. University, Tirunelveli, India

Prof. (Dr.) Nikos Passas

Professor of Criminology & Criminal Justice

College of Social Sciences and Humanities

Northeastern University, Boston, USA

Volume 46 & 47, 2018-2019

Indian

Journal of

Criminology

Contents

Articles

The Quest for Truth in Criminal Justice- Revisiting the Malimath

Committee Recommendations

Ankita Chakraborty & Dipa Dube

1

Redesigning of Urban Safety Measurement Model Analysing Crime

Standpoints

Rajesh Kumar

16

Attitude to Prison Reforms: An Empirical Survey

Upneet Lalli

32

Recidivism among Prisoners in Tihar Jail and Contributing Factors:

A Qualitative Study

S. Manikandan and K.Jaishankar

46

Adjustment of Child in Conflict with Law: An Empirical Study

Lakshmi Pandey

58

Rationality or Opportunity: What Matters in Crime? A Descriptive

Analysis of Property Crimes Reported by Electronic Media in Chennai

City and its Outskirts.

K. Kuralarasan and M. Priyamvadha

66

Rehabilitation and Reintegration Possibilities for Rape Victims in India

Vibha Hetu

79

Incarcerated Motherhood under the Purview of Policies, Prison

Reforms and Reintegration

Pearly Paul and Intezar Khan

106

An Empirical Study on Bullying and Sexual Harassment at Workplace

Shubhangi Srivastava and Priyanka Kacker

122

INDIAN JOURNAL OF CRIMINOLOGY - Volume 46 & 47 2018-2019

REDESIGNING OF URBAN SAFETY MEASUREMENT MODEL

ANALYSING CRIME STANDPOINTS

Dr. Rajesh Kumar*

Abstract

The objective of this study is to present a blueprint; how to test the safety status of a city. It applies the proposed model to investigate the first list of Indian smart cities. It measures the safety status of select cities by analyzing the crime standpoints and attempts to enquire; Are smart cities safe cities? The method creates five crimes categories based on relative nature and severity. Further, it assigns different value points for different crime categories to develop the city’s safety point as a determinant which constructs a more balanced tool. The study prima facie confirms that none city found safe as per the scale set forth. The applied model is one of the modules which may supplement to a broader assessment framework. Through a review of studies, it endorses the identical elements that will enrich the evaluation process and also be the topics of future investigations.

KEY WORDS

Urban safety; Measurement model; Indian smart cities; Ranking of safe cities; Crime statistics.

Introduction

The growth of urbanization is taking place at a faster rate in India since before its independence. The population of an urban area was 11.4 percent according to 1901 census which increased to 28.53 percent in 2001 and crossed 31.15 percent; according to 2011 census 377 million people living in urban areas and in 2018 this number rose to 449 million, accounting for 33.2 percent of India’s population and urban population projects to increase to about 600 million by 2030. (Worldometers, 2018)

The two peculiarities of congested cities attract attention; first, several slums rise rapidly, 37.14 percent decadal growth recorded in the number of ‘slum’ households. Almost two-thirds of statutory towns in India have ‘slums’ and 13.75 million households live in them. (Housing and Land Rights Network, 2014, p.1) By 2017, slum population of India will surge to

104 million, this means urban planners will face escalating challenges and consequences ahead as these slums will mostly proliferate in sleepy towns (Das, 2013) Contrary to above, GoI (Government of India) launched SCM (Smart Cities Mission) in June 2015 to develop 100 smart cities nationwide with the budget of 2031.72 billion for infrastructure development. However, it will impact 99630069 lives (Ministry of Housing and Urban Affairs, 2015) but eventually, the situation is awfully weird.

The village dweller moving towards an urban area because of many reasons, primarily for a livelihood. While they move to a city, an obvious question arises in their mind. How much is this city safe? How much will they be safe in the city? The individual keeps the safety as a topmost priority and in that case, safety studies influence their mind. To find an answer to these questions, it becomes inevitable to understand the

*FORE School of Management New Delhi, ORCID No. 0000-0002-8735-3540, Email: [email protected]



safety evaluation process. Their concerns have to be addressed appropriately. Hence, the primary aim of this study is to develop a basic and reliable evaluation approach.

Objectives of the Study

The explicit objectives of this study are to highlight the present crime statistics of select cities; propose a model to evaluate the safety status of a city; find overall CSP (City’s Safety Points) as a determinant by categorising crimes by nature and severity and identify a few more supportive components for evaluation.

Review of Literature

The population density and compactness, (Lehmann, 2016, p.2) and crime rate, both are significant components for safety and security of cities. The twelve select smart cities average populate 33.9 lakhs; (Smart Cities Mission, 2015, June) ICC (Incidence of Cognizable Crimes) -12101 and RCC (Rate of Cognizable Crimes)-454 each city whereas the incidence of national cognizable crimes is 7326099 with AIR (All India Rate of Cognizable Crimes) of crimes-581.8. These cities embrace 40680000 lives that’s 3.36 percent of national (1210854977) and 10.79 percent of urban (377106125) respectively. (National Crime Records Bureau, 2015).

A few evaluations study on the city’s safety and ratings are available. Further, notice that these studies result from spontaneous action, and later such studies become self-victim due to the dearth of standard operating procedures. The investigators raise questions on the validity of parameters and instruments used for the studies. Several studies examined by various viewpoints but none found suits to the Indian context. A study presents that at the aggregate level, reporting efficiency stood around 73 % (27

% under-reporting) (Chaudhuri, Chaudhuri and Kumbharkar, 2015, p.13) which shows an under-reporting of cases comprises a high ratio. Another study shows that reduced crime rates improve public safety

and general citizen well-being, (IHS Markit, 2017) which highlights the significance of crime rate, used as a standard index. Hence, instead of numerous contrary facts, the data on crime remains a prime tool and rate of crimes applied as an index for such evaluation studies. In 1958, the FBI created a national crime index to serve as a general indicator of criminality in the United States. (Federal Bureau of Investigation, 2004) An international study based on an index composed of forty-nine quantitative and thirty-one qualitative indicators. These indicators are a diverse mix of four thematic categories: on the relative level of safety of four main categories, for example, digital security, health security, infrastructure safety, and personal safety. (Economist Intelligence Unit, 2017) But this study applies different assessment tools than the EIU study. Ironically, there is no such basic evaluation research work found which have used standardized parameters.

The traditional crime rate does not provide information on the overall seriousness of crimes, further propose Crime Severity Index for Canada using data on police-reported crime by considering the relative severity of a particular crime compared to other crimes. The seriousness of each offense (weights) is derived from actual sentences handed down by courts. (Wallace, et al. 2009) The conventional crime evaluation determines by the RCC but this study develops nRCC (new Rate of Cognizable Crimes); allocates different value points to different categories of crimes by assessing their severity.

Methods

A present study is a well-defined act of quantitative research measuring the safety status of a city. It follows the descriptive, and analysis method and present results in order.

Source of Data

The first list of smart cities declared by the SCM, Ministry of Housing and Urban


Affairs, GoI recorded from its website whereas the study restricts to smart cities. It records the prerequisite crime data from the annual report: ‘Crime in India 2015 Statistics’. (National Crime Records Bureau, 2015) It uses the data figures mentioned as RCC under different crime heads during 2015 for both IPC (Indian Penal Code) (refer table 4) and SLL (Special and Local Laws) (refer table 5) comprising 52 and 56 crime heads respectively. It excludes some crime heads which comprises a zero value and reflects no relevance form the study.

Data and Study Limitations

Many questions arise while conducting this study that which component: digital security, health security, infrastructure safety, and personal safety’ to analysis. After a review of the literature, the study observes that data on personal safety is more significant among above all components. Further, the data on personal safety reviewed; i.e., pre-measured data to prevent crime; data on a post-crime investigation and policing procedures; and trial, judgment and convictions rate, etc. Apart from the above, the data on other facets which may indirectly influence the

safety, i.e., preventive data on the natural disaster, terrorist attacks, human errors etc. reviewed, and as noticed that these facets comprise insufficient data. Ultimately, the study focuses on crimes data where a uniform data found in an annual report ‘Crime in India’ which is one of the prime documents on crime statistics in India. The rate of crime is a standard unit for measurement; crime reported per lakh person in the target population. It uses the data on cognizable crimes as it is, available in the report and RCC considered as an index for calculations and comparisons.

The SCM declared smart cities on 28 January 2016 on the factsheet of the year 2015 that also included safety and security aspects. Therefore, the ground realities of safety and security of these cities must test. Hence, the study accumulates the data of the select cities for the same year. The eight cities out of twenty smart cities comprise inadequate data, focused the study to twelve cities only.

As compare in table 1; the ICC of cities; Jaipur, Indore, and Ahmedabad gained top unsafe rank; in order to RCC, the rank order

Table 1 - List of cities in order of RCC.

Smart City Rank*

City* ICC# Safety Rank: ICC# index

Population# (In Lakhs)

RCC# Safety Rank

:RCC# index

4 SU-Surat 3985 2 45.8 86.9 1

18 CH-Chennai 13422 6 87.0 154.3 2

13 CB-Coimbatore 3827 1 21.5 177.9 3

19 LD-Ludhiana 4012 3 16.1 248.6 4

6 AM-Ahmedabad 15964 10 63.5 251.3 5

2 PN-Pune 15349 9 50.5 303.9 6

8 VP-Visakhapatnam 6005 4 17.3 347.1 7

5 KC-Kochi 13781 7 21.2 650.7 8

7 JB-Jabalpur 9253 5 12.7 729.7 9

20 BP-Bhopal 14857 8 18.8 789.0 10

11 ID-Indore, 18463 11 21.7 852.0 11

3 JP-Jaipur 26288 12 30.7 855.5 12

Source: * Smart Cities Mission, (2015) # Crime in India 2015 Statistics


changed to Jaipur, Indore, and Bhopal and so on as table 1 depicts. But equal weight- age or equalized RCC for all crimes is not justifiable which half-finished evaluation process appears. A heinous or accidental crime can’t be equally weighted; allocating a different value to a different nature of crimes considering its severity become vital.

Design and Development of Assessment Model

The following assumed categories of crimes assigned the value points under their severity. The study carefully drives the severity (value) of each crime by weighing the actual award of punishment under IPC and SLL; further on the merit of the expert’s advice.

First; a list of eligible crimes prepared separately for SLP and SLL along with their AIR and RCC. AIR of cognizable crimes denoted as the national base index for the rate of crime. Then as below-proposed, it

uses the formula to get nRCC under the above value points.

Table 2 - Calculations of CSP.

1. Average RCC = AIR

Value points of crime category

RCC

2. nRCC = Average RCC

For example, Average RCC = (AIR of Murder) 2.6 / Value points of crime category 5=0.52 nRCC= (RCC of Ahmedabad) 1.4 / (Average of RCC) 0.52= 2.69 (Please refer table 4)

The above formula is a new experiment to gain nRCC. The same results can be carried out by the following formula also.

3. i.e., murder in Ahmedabad (1.4 / 2.6 X 5 = 2.69)

Analysis and Discussion

By applying the proposed formula, nRCC of each city for each crime under IPC and SLL separately (refer table 4 and 5 respectively)

retrieved; overall nRCC corroborated to gain CSP for ranking of cities in order to determine the safety status. (See table -3)

S.N. IPC SLL Overall

CSP Score in + CSP Score in - CSP Score in + CSP Score in - CSP Score in + CSP Score in -

1 94.02 -39.11 65.64 -0.01 159.66 -7.37

2 75.21 -79.44 82.60 -6.90 157.81 -17.19

3 58.24 -46.71 73.99 -68.26 58.23 -33.33

4 34.12 -106.86 46.11 -8.52 34.88 -57.55

5 68.36 -76.91 38.96 -35.17 27.22 -67.9

6 1.15 -10.84 0.1 -254.55

7 17.98 -177.64

Av

Mn

349.08/7

=49.87

-349.03/5

= 69.81

307.3/5

=61.46

-307.34/7

= 43.91

-437.9/6

= -72.98

-437.89/6

= -72.98

Crime Most Heinous Heinous Major Minor Incidental

Category Crimes Crimes Crimes Crimes Minor Crimes

Value Points 5 4 3 2 1


The Average Mean of all cities nRCC carried out, i.e., 147.24 for IPC; 129.50 for SLL and 276.74 for overall.

The average mean (AvMn) of overall nRCC:

4. nRCC (IPC)+nRCC (SLL)=overall nRCC calculated by applying the following formula, i.e.

5.

Average mean = ∑nRCC (3320.87)

city counts (12)

(Overall) (see table 3; similarly, AvMn

calculated for IPC and SLL)

Further, nRCC is converted into CSP to determine the safety status of the cities.

6. (See table 3; similarly, CSP of other cities calculated as per IPC, SLL and overall)

7. a)

Average mean of overall city’s CSP in (+)

= ∑of city’s CSP (437.90)

city counts (6)

b)

Average mean of city’s CSP in (-)

= ∑of city’s CSP (-437.89)

city counts (6)

Similarly, the above method applied to get nRCC and CSP for both IPC and SLL.

Refer table 2: the seven cities found CSP in + and five cities in – under IPC; five cities found CSP in + and seven cities – under SLL and as overall equal cities six found in + and – both.

Further, the cities divided into following five safety statuses as per the gained CSP.

Safe City Status

It assumes the city’s safety level as per IPC as…

If CSP=0 then the city is considered as ‘Safe’

If 49.87<CSP then the city is considered as ‘Relatively Safe’

If 0<CSP≤49.87 then the city is considered as ‘Unsafe’

If 0<CSP≤-69.81 then the city is considered as ‘Relatively Unsafe’

If -69.81<CSP then the city is considered as ‘More Unsafe’

It assumes the city’s safety level as per SLL as…






It assumes an overall city’s safety level as…






The CSP score assists the comparison among cities and ranks them in order as depicted in table 3. An ideal condition assumed for a safe city; the city which obtained zero (0)

Safe Relatively Safe Unsafe Relatively Unsafe More Unsafe


Table 3 - Overall safety status of smart cities in order.

IPC SLL Overall

Rank City nRCC# CSP^ Status nRCC# CSP^ Status nRCC# CSP^ Status Rank

4 SU 53.22 94.02 Relatively 63.86 65.64 Relatively 117.08 159.66 Relatively 1 Safe Safe Safe

6 AM 72.03 75.21 Relatively 46.90 82.60 Relatively 118.93 157.81 Relatively 2 Safe Safe Safe

18 CH 89.00 58.24 Relatively 129.51 -0.01 Relatively 218.51 58.23 Relatively 3 Safe Safe Safe

2 PN 186.35 -39.11 Relatively 55.51 73.99 Relatively 241.86 34.88 Relatively 4 Safe Safe Safe

8 VP 113.12 34.12 Unsafe 136.40 -6.90 Relatively 249.52 27.22 Unsafe 5 Unsafe

13 CB 78.88 68.36 Relatively 197.76 -68.26 More 276.64 0.1 Unsafe 6 Safe Unsafe

19 LD 146.09 1.15 Unsafe 138.02 -8.52 Relatively 284.11 -7.37 Relatively 7 Unsafe Unsafe

5 KC 129.26 17.98 Unsafe 164.67 -35.17 Relatively 293.93 -17.19 Relatively 8 Unsafe Unsafe

11 ID 226.68 -79.44 More 83.39 46.11 Unsafe 310.07 -33.33 Relatively 9 Unsafe Unsafe

7 JB 193.95 -46.71 Relatively 140.34 -10.84 Relatively 334.29 -57.55 Relatively 10 Unsafe Unsafe Unsafe

20 BP 254.10 -106.86 More 90.54 38.96 Unsafe 344.64 -67.9 Relatively 11 Unsafe Unsafe

3 JP 224.15 -76.91 More 307.14 -177.64 More 531.29 -254.55 More 12 Unsafe Unsafe Unsafe

Av

Mn

1766.83/1 1554.04/1 3320.87/1

2=147.24 2=129.50 2=276.74

*Smart Cities Mission, (2015) Ranking; # See table 4 and 5; ^ See table 2

CSP score considered a safe city and zero (0) CSP score set as an index for the safe city. The obtained CSP score by the cities in plus and in minus appropriately assigned safety status in table 3. The city’s safety status presented as per the obtained CSP score for IPC, SLL and overall separately. It depicts the safety level in decreasing order from safe to unsafe. (From city SU to JP) Prima facie, none city found safe as per the scale set forth. Inconsistency noticed in smart city rank and safety status of the cities while comparing CSP score as per the IPC, SLL and overall.

Concluding Remarks

The study observes no consistency in the

rank of a smart city and a safe city. Hence, the rank of smart cities irrelevant to their status of safety. While comparing, two safer cities as per RCC of table 1 found a place in the top three safer cities as per nRCC in table 3. Identically all five top unsafe cities of table 1 found the place among top five unsafe cities in table 3 but in a changed order. Hence, results of this study are along the line which proved its worth by filling the proportional gaps which observed in table 1 and by applied to the proposed model; it presents refined results in table

3. By applying the model anyone can find the safety status of a particular city and can rank them by comparing among other


uniform cities. The method used in this study may be an example to other similar studies or will add value to more exhaustive studies. The study will draw the attention of think tanks, government agencies, and individuals who involve in research, policy making, and execution of decisions. Further, it will encourage them to develop benchmarks for the evaluation processes.

It is acknowledged that the results are significant even though there are many limitations to the study. It recommends a holistic evaluation framework comprising personal safety, digital security, health security, infrastructure safety, a safety measure for the natural disaster, and human errors, etc. Further, an integrated uniform crime reporting platform (to lodge FIR) is in the want of dealing with under-reported cases. Standardization of crime statistics recording and reporting is substantially essential to compare identical and contrary

figures for better evaluation model. Through the literature review, it identifies the above components that may enhance the evaluation procedure and could be the topics for future research. Further, standardization of crime data from local to international level is highly requisite for a more structured and elaborative evaluation method.

* Due to non-availability of AIR, lowest RCC of the city considered as AIR for that particular crime.

Note: 1. The calculated values are rounded up to one decimal and two decimals for RCC and nRCC (in bracket) respectively; hence an approximate value is used for analysis.

2. While conducting a study for other cities, existing crime may be removed or added new crime(s), sub-crime(s) or category as require.


REFERENCES

• Chaudhuri, K., Chowdhury, P., and Kumbhakar, S. C. (2015). ‘Crime in India: Specification and estimation of violent crime index’ Journal of Productivity Analysis, 43(1), 13-28. Retrieved, http://dx.doi.org/10.1007/s11123-014-0398-7 Accessed: 08 October 2018.

• Das, Dipak Kumar (2013). ‘By 2017, India’s slum population will rise to 104 million’, The Times of India (New Delhi) 20 August 2013. Retrieved, https://timesofindia. indiatimes.com/india/By-2017-Indias-slum-population-will-rise-to-104-million/ articleshow/21927474.cms Accessed: 13 October 2018

• Economist Intelligence Unit. Safe Cities Index 2017: Security in a rapidly urbanising world. Retrieved, http://safecities.economist.com/safe-cities-index-2017 Accessed: 05 October 2018.

• Federal Bureau of Investigation, U.S. Department of Justice, (2004). Uniform Crime Reporting Handbook. Revised. Retrieved, https://www2.fbi.gov/ucr/handbook/ ucrhandbook04.pdf Accessed: 15 October 2018

• Housing and Land Rights Network, (2014). The human rights to adequate housing and land in India: status update 2013 [online]. Retrieved, https://www.hlrn.org.in/documents/ Housing_and_Land_Status_Update_2013.pdf Accessed: 03 October 2018

• IHS Markit (2017). Whitepaper: The Benefits of Safe Cities: Safer Cities Creating a Better Life. [online]. Retrieved,https://cdn.ihs.com/www/Technology/Security/IHS_Markit- Benefits_of_Safe_Cities_WhitePaper.pdf Accessed: 15 October 2018

• Lehmann, S. (2016), ‘Sustainable urbanism: Towards a framework for quality and optimal density?’ Future Cities Environment, 2:8, 2-13 Retrieved, https:// futurecitiesandenvironment.com/articles/10.1186/s40984-016-0021-3/ Accessed: 18 October 2018

• Ministry of Housing and Urban Affairs (2015), SMARTNET: Smart Cities Mission, Available at: https://smartnet.niua.org/smart-cities-network Accessed 04 October 2018

• National Crime Records Bureau. (2015). Crime in India 2015. Retrieved, http://ncrb.gov. in. Accessed: 03 October 2018

• Smart Cities Mission. (2015, June). Statement and Guidelines. Retrieved, http:// smartcities.gov.in/upload/uploadfiles/files/SmartCityGuidelines(1).pdf Accessed: 05 October 2018

• Wallace, M., Turner, J., Matarazzo, A. and Babyak, C. (2009). Measuring Crime in Canada: Introducing the Crime Severity Index and Improvements to the Uniform Crime Reporting Survey 2009. Statistics Canada Catalogue no. 85-004-X. Ottawa. Retrieved,https:// www150.statcan.gc.ca/n1/en/pub/85-004-x/85-004x200900-eng.pdf?st=VC6Hc JCF Accessed: 15 October 2018

• Worldometers. Retrieved, https://www.worldometers.info/world-population/india- population. Accessed: 15 October 2018

Citation for this article.

Rajesh Kumar. Redesigning of Urban Safety Measurement Model Analysing Crime

Standpoints, Indian Journal of Criminology. Vol. 46 & 47; 2018-2019, p16-31.

http://dx.doi.org/10.1007/s11123-014-0398-7

http://safecities.economist.com/safe-cities-index-2017

http://www.hlrn.org.in/documents/

http://www.hlrn.org.in/documents/

http://ncrb.gov/

http://www.worldometers.info/world-population/india-


Table 4: IPC-Crimes, Sub-crimes with AIR, Value points of crime category, and city’s RCC with nRCC in (bracket)

Sr Crimes Sub-Crimes AIR Value

points AM BP CB CH ID JB JP KC LD PN SU VP

1

Murder

Murders

2.6

5

1.4

(2.69)

2.9

(5.58)

1.2

(2.31)

1.6

(3.08)

3.2

(6.15)

3.2

(6.15)

3.7

(7.12)

0.5

(0.96)

4.5

(8.65)

2.5

(4.81)

2.2

(4.23)

1.4

(2.69)

2

Attempt to Commit

Murder

3.7

4

0.8

(0.86)

4.0

(4.32)

1.8

(1.95)

2.4

(2.59)

9.1

(9.84)

9.7

(10.49

)

3.4

(3.68)

0.9

(0.97)

4.2

(4.54)

3.6

(3.89)

0.4

(0.43)

2.8

(3.03)

3

Homicide

Culpable Homicide

not amounting to

Murder

0.3

4

0.1

(1.33)

0.3

(4)

0

(0)

0.1

(1.33)

0

(0)

0.3

(4)

0.2

(2.67)

0.1

(1.33)

0.7

(9.33)

0.2

(2.67)

0.1

(1.33)

0

(0)

4

Attempt to Commit

Culpable Homicide

0.5

4

0

(0)

0.5

(4)

0

(0)

0

(0)

0.1

(0.8)

0.1

(0.8)

0

(0)

1.1

(8.8)

0

(0)

0

(0)

0

(0)

0

(0)

5 Rape Rape 5.7 5 0.9 7.1 0.1 0.3 3.5 6.5 9.1 2.4 6.3 5.3 0.9 5

(0.79) (6.23) (0.09) (0.26) (3.07) (5.7) (7.98) (2.11) (5.53) (4.65) (0.79) (4.39)

6

Attempts to Commit

Rape

0.7

4

0

(0)

0.2

(1.14)

0

(0)

0

(0)

0.1

(0.57)

0.2

(1.14)

0.1

(0.57)

0

(0)

1.1

(6.29)

0

(0)

0

(0)

0.1

(0.57)

7

Kidnapping &

Abduction

for Murder

0.1

3

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

8

for Ransom

0.1

3

0.1

(4)

0

(0)

0

(0)

0.1

(4)

0

(0)

0

(0)

0.1

(4)

0

(0)

0

(0)

0.2

(8)

0.2

(8)

0

(0)

9

of Women to Compel

her for Marriage

5.2

3

3.1

(2.38)

11.9

(9.15)

0

(0)

0.1

(0.08)

2.6

(2)

7.3

(5.62)

2.8

(2.15)

0.4

(0.31)

13.4

(10.31)

0.8

(0.62)

1.5

(1.15)

0

(0)

10

Other Kidnapping &

Abduction

3.9

3

2.1

(1.62)

10.9

(8.38)

0.3

(0.23)

0.3

(0.23)

18.2

(14)

21.3

(16.38

)

17.6

(13.54)

0.2

(0.15)

3.6

(2.77)

13

(10)

3.7

(2.85)

10.9

(8.38)

11

Dacoity

Dacoity with Murder

0

5

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

12

Dacoity

0.3

4

0.1

(1.33)

0.1

(1.33)

0.2

(2.67)

0.1

(1.33)

0.2

(2.67)

0.2

(2.67)

0

(0)

0.4

(5.33)

0.1

(1.33)

0.8

(10.67)

0.4

(5.33)

0

(0)


13

Preparation and

Assembly for Dacoity

0.3

2

0

(0)

0.5

(3.33)

0.1

(0.67)

0

(0)

0.6

(4)

0.2

(1.33)

0.2

(1.33)

0.3

(2)

1.9

(12.67)

0.6

(4)

0.1

(0.67)

0

(0)

14

Robbery

2.9

4

2.0

(2.76)

7.9

(10.9)

5.6

(7.72)

0.8

(1.1)

11.9

(16.41)

8

(11.03

)

10.2

(14.07)

1.6

(2.21)

1.1

(1.52)

14.5

(20)

0.7

(0.97)

1.7

(2.34)

15

Criminal

Trespass /

Burglary

Criminal Trespass /

Burglary

6.9

3

6.7

(2.91)

0

(0)

5.0

(2.17)

2.5

(1.09)

52.6

(22.87)

29.7

(12.91

)

33.6

(14.61)

3.4

(1.48)

0.3

(0.13)

16.9

(7.35)

4.5

(1.96)

16.0

(6.96)

16

House Trespass &

House Breaking

2.2

3

2.3

(3.14)

47.2

(64.36)

1.3

(1.77)

0.6

(0.82)

0

(0)

6.5

(8.86)

7.1

(9.68)

1.2

(1.64)

13.8

(18.82)

6.7

(9.14)

0.7

(0.95)

2.9

(3.95)

17

Theft

Auto Theft

15.8

3

26.8

(5.09)

126.9

(24.09)

9.6

(1.82)

2.3

(0.44)

183.1

(34.77)

42.8

(8.13)

177.4

(33.68)

5.2

(0.99)

10.7

(2.03)

53.3

(10.12)

19

(3.61)

20.8

(3.95)

18

Other Theft

21.3

2

12.4

(1.16)

40.4

(3.79)

12.8

(1.20)

9.8

(0.92)

68.7

(6.45)

26.1

(2.45)

63.1

(5.92)

10.1

(0.95)

24.8

(2.33)

46.5

(4.37)

6.4

(0.6)

37.7

(3.54)

19

Unlawful Assembly

0.9

2

0.4

(0.89)

0

(0)

2.4

(5.3)

2.6

(5.78)

0

(0)

0

(0)

9

(20)

5.5

(12.22)

0

(0)

0.1

(0.22)

0.1

(0.22)

0

(0)

20

Riots

5.2

4

1.9

(1.46)

2.8

(2.15)

1.8

(1.38)

1.7

(1.31)

2.2

(1.69)

5

(3.85)

2.3

(1.77)

2

(1.54)

0

(0)

5.1

(3.92)

2.5

(1.92)

0.3

(0.23)

21

Criminal Breach of

Trust

1.5

3

2.6

(5.20)

1.7

(3.4)

0.6

(1.2)

0.8

(1.6)

2.0

(4)

0.6

(1.2)

6

(12)

0.8

(1.6)

2.3

(4.6)

2.1

(4.2)

0.5

(1)

3.9

(7.8)

22

Cheating

9.2

1

2.8

(0.30)

9.0

(0.98)

7.2

(0.78)

3.1

(0.34)

6.0

(0.65)

6.9

(0.75)

176.5

(19.78)

26.6

(2.89)

27.9

(3.03)

15.5

(1.68)

7.8

(0.85)

29.9

(3.25)

23

Forgery

1.1

2

0.4

(0.73)

0.1

(0.18)

0.1

(0.18)

1.7

(3.09)

1.2

(2.18)

0.4

(0.73)

0.1

(0.18)

0.5

(0.91)

0.1

(0.18)

0.1

(0.18)

0.8

(1.45)

0.6

(1.09)

24

Counterfeiting

Offences Reltd to

Coin/ Government

Stamp/ Currency &

Bank Notes

0.1

3

0.1

(3)

0.5

(15)

0

(0)

0.8

(24)

0.2

(6)

0

(0)

0

(0)

0.3

(9)

0

(0)

0.2

(6)

0.1

(3)

0

(0)

25

Arson

0.8

4

0.2

(1)

1.4

(7)

0.6

(3)

0.2

(1)

2.6

(13)

0.5

(2.5)

0.7

(3.5)

0.3

(1.5)

0.4

(2)

1.1

(5.5)

0.1

(0.5)

0.9

(4.5)

26

Grievous Hurt

Grievous Hurt

7.4

3

2.7

(1.09)

1.4

(0.57)

1.0

(0.41)

0.5

(0.2)

3.4

(1.38)

7.3

(2.96)

0.3

(0.12)

3.9

(1.58)

12.3

(4.99)

12.9

(5.23)

3.8

(1.54)

4.2

(1.7)


27

Acid Attack

0

4

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0.1

(0)

0

(0)

0

(0)

0.1

(0)

28

Attempt to Acid

Attack

0

3

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

29

Dowry Deaths

1.3

5

0

(0)

0.5

(1.92)

0

(0)

0.1

(0.38)

0.8

(3.08)

1

(3.85)

1

(3.85)

0

(0)

0.2

(0.77)

0.3

(1.15)

0

(0)

0.4

(1.54)

30

Assault on

Women with

Intent to

Outrage her

Modesty

Sexual Harassment

4.0

4

1.2

(1.20)

17.1

(17.1)

0

(0)

0.1

(0.1)

4.2

(4.2)

5.3

(5.3)

1.6

(1.6)

6.6

(6.6)

3

(3)

5.8

(5.8)

0.9

(0.9)

3.8

(3.8)

31

Use of Criminal

Force With Intent to

Disrobe

1.4

3

0.1

(0.21)

0

(0)

0

(0)

0

(0)

0.1

(0.21)

0.9

(1.93)

0.8

(1.71)

0

(0)

0.8

(1.71)

0.4

(0.86)

0

(0)

1.4

(3)

32

Voyeurism

0.1

1

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0.3

(3)

0.1

(1)

0

(0)

0.1

(1)

0.1

(1)

0

(0)

0.4

(4)

33

Stalking

1.0

2

0.3

(0.60)

0

(0)

0

(0)

0

(0)

1

(2)

3.2

(6.4)

0.7

(1.4)

0

(0)

0.4

(0.8)

3

(6)

0.1

(0.2)

2.2

(4.4)

34 Others 7.0 1 0.7

(0.10)

0

(0)

0.6

(0.09)

0.6

(0.09)

4.5

(0.64)

5.6

(0.8)

7.4

(1.06)

0

(0)

3.8

(0.54)

4.5

(0.64)

0.1

(0.01)

7.1

(1.01)

35

Insult to

Modesty of

Women

At Office Premises

0

2

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

36

Other Places Related

to Work

0.1

2

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0.4

(8)

0

(0)

0

(0)

37

In Public Transport

System

0.1

2

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

38

Places other Than

above Places

1.2

2

0

(0)

1.0

(1.67)

0

(0)

0

(0)

4.8

(8)

1.5

(2.5)

0

(0)

0.9

(1.5)

0.4

(0.67)

1

(1.67)

0

(0)

0.5

(0.83)

39

Cruelty by Husband

or His Relatives

18.7

3

9.4

(1.51)

16.7

(2.68)

1.9

(0.30)

2.3

(0.37)

9.9

(1.59)

11.1

(1.78)

36.2

(5.81)

5.8

(0.93)

7.9

(1.27)

7.5

(1.2)

5.7

(0.91)

22.1

(3.55)

40

Importation of Girls

from Foreign Country

0

3

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

41

Causing

Deaths by

Negligence

Deaths Due to Rash /

Negligent Driving

10.3

4

5.8

(2.25)

8.8

(3.42)

12.0

(4.66)

10.0

(3.88)

10.3

(4)

17.6

(6.83)

28.2

(10.95)

6.4

(2.49)

17.0

(6.6)

9.2

(3.57)

5.6

(2.17)

22.4

(8.7)

42 Deaths Due to other 0.4 5 0.1 0.8 1.3 1.2 1 1.5 0.2 0.1 0 0.8 0 1


Causes (12.5) (10) (16.25

)

(15) (12.5) (18.76

)

(2.5) (12.5) (0) (10) (0) (12.5)

43

Offences

Against State

Sedition

0

4 0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

44

Others

0

3 0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

45

Offences

Promo -ting

Enmity

Between

Different

Groups

On Ground of

Religion, Race, Birth

Place, etc.

0.1*

3

0

(0)

0.1

(3)

0.4

(12)

0.1

(3)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

46

Imputation,

Assertions

Prejudicial to

National Integration

0

4

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

47

Extortion

0.8

4 0.7

(3.5)

0.6

(3)

0.9

(4.5)

0.9

(4.5)

1

(5)

2.1

(10.5)

0.5

(2.5)

0.3

(1.5)

0.5

(2.5)

1.4

(7)

0.3

(1.5)

0.6

(3)

48 Disclosure of Identity 0 2 0 0 0 0 0 0 0 0 0 0 0 0

of Victims (0) (0) (0) (0) (0) (0) (0) (0) (0) (0) (0) (0)

49

Causing Injuries

under Rash Driving/

Road Rage

35.8

3

37.9

(3.18)

178.9

(14.99)

58.3

(4.89)

74.9

(6.28)

198.8

(16.66)

159.2

(13.34

)

76.1

(6.36)

495.8

(41.55)

0.2

(0.02)

26

(2.18)

12.2

(1.02)

80.1

(6.71)

50

Human Trafficking

0.1

4 0

(0)

0

(0)

0

(0)

0

(0)

0

(4)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

0

(0)

51 Unnatural Offences

0.1

3 0

(0)

0.3

(9)

0

(0)

0

(0)

0.2

(6)

0.2

(0.6)

0.1

(3)

0

(0)

0.8

(24)

0.3

(9)

0.1

(3)

0

(0)

52

Other IPC Crimes

77.4

2 125.0

(3.23)

286.8

(7.41)

50.4

(1.3)

31.5

(0.81)

243.6

(6.29)

337.1

(8.71)

179.2

(4.63)

67.0

(1.73)

83.7

(2.16)

41.1

(1.06)

5.3

(0.14)

65.8

(1.7)

Total nRCC

(72.03

)

(254.1

0)

(78.88

)

(89) (226.6

8)

(193.9

5)

(224.15

)

(129.2

6)

(146.0

9)

(186.3

5)

(53.5

2)

(113.12

)


Table 5: SLL-Crimes with AIR, Value points of crime category, and city’s RCC with nRCC in (bracket)

Sr Crimes AIR

Value

points

AM BP CB CH ID JB JP KC LD PN SU VP

1

Arms Act, 1959

4.2

3

1.6

(1.14)

49.6

(35.43

)

0

0.1

(0.07)

39.6

(28.29

)

31.0

(22.14

)

7.8

(5.57)

0.2

(0.14

2.3

(1.64)

2.2

(1.57)

0.5

(0.36)

0.1

(0.07)

2

NDPS Act

4

4

0.1

(0.1)

0.8

(0.8)

4.8

(4.8)

1.4

(1.4)

0.9

(0.9)

4

(4)

0.7

(0.7)

30.9

(30.9)

30.2

(30.2)

1.1

(1.10)

0.1

(0.1)

1.7

(1.7)

3

Gambling Act

10.3

2

20.8

(4.04)

72.7

(14.12

)

14.2

(2.76)

2.6

(0.5)

42.9

(8.33)

103.9

(20.17

)

44.2

(8.58)

2.3

(0.45)

22.7

(4.41)

8.2

(1.59)

17.9

(3.48)

1.4

(0.27)

4

Excise Act

16.4

2

0

132.7

(16.18

)

0

0

58.2

(7.1)

133.2

(16.34

)

32.8

(4)

0

26.8

(3.27)

0

0

3.1

(0.38)

5

Prohibition Act

39.8

2

205.1

(10.46

)

0

124.5

(6.35)

101.1

(5.16)

0

0

0

191.8

(9.79)

0

27.2

(1.39)

903.9

(46.12

)

0

6

Explosives & Explosive

Substances Act

0.3

4

0.9

(12)

0.1

(1.33)

0.1

(1.33)

0.1

(1.33)

0.5

(6.67)

3.9

(52)

0.5

(6.67)

0.1

(1.33)

0

0

0.3

(4)

0.5

(6.67)

7

Immoral Traffic (Prevention)

Act

0.2

4

0.1

(2)

0.2

(4)

1.7

(34)

2.3

(46)

0.4

(8)

0

0.7

(14)

2.8

(56)

1.3

(26)

1.2

(24)

0

2.0

(40)

8

Indian Railways Act

0.1*

2

0

0

0

0

0

0

0

0.1

(2)

0

0

0

0

9

Registration of Foreigners Act

0.1*

3

0

0

0

0

0

0

0.1

(3)

0.1

(3)

0

0

0

0

10

Protection of Civil Rights Act

0.2*

2

0

0

0

0

0

0

0

0

0

0.2

(2)

0

0

11

Passport Act

0.1

2

0

0.1

(2)

0

0.8

(16)

0

0

0.1

(2)

0.2

(4)

0

0

0

0

12 Essential Commodities Act 0.4 2 0 0.6 0 0 0.3 0 0.1 0.8 1.1 0.7 0 0.3

(3) (1.5) (0.5) (4) (5.5) (3.5) (1.5)


13

Antiquities & Art Treasures Act,

1972

0

2

0

0

0

0

0

0

0

0

0

0

0

0

14

Dowry Prohibition Act

1.6

3

0

0

0

0

0

0.9

(1.69)

0

0

0

0

0

0

15

Indecent Representation of

Women (Prohibition) Act

0

3

0

0

0

0

0

0

0

0

0

0

0

0

16

Copy Right Act, 1957

0.4

2

0.6

(3)

0.7

(3.5)

6.2

(31)

4.8

(24)

0.2

(1)

0.4

(2)

0.9

(4.5)

0.5

(2.5)

2.5

(12.5)

1.0

(5)

0.3

(1.5)

0.8

(4)

17

Protection of Children from

Sexual Offences Act

3.3

4

3.0

(3.64)

5.5

(6.67)

1.3

(1.58)

1.6

(1.94)

8.7

(10.55

)

10.7

(12.97

)

0.5

(0.61)

0.4

(0.48)

0

0

3.0

(3.64)

0.1

(0.12)

18

SC/ST (Prevention of

Atrocities) Act

2.2

2

0.3

(0.27)

0

0

0.1

(0.09)

0

0

0.4

(0.36)

0.1

(0.09)

0.2

(0.18)

0.1

(0.09)

0

7.9

(7.18)

19

Forest Act

0.3

3

0

0

0

0

0

0

0.4

(4)

0

0.1

(1)

0

0

0

20

Prohibition of Child Marriage

Act

0.1

2

0

0

0

0

0

0

0

0

0.1

(2)

0

0

0.1

(2)

21

Protection of Women From

Domestic Violence Act

0.1

3

0

0

0

0

0

0

0

0.2

(6)

0

0

0

0

22

Information Technology Act

0.6

3

0.4

(2)

0.7

(3.5)

0.4

(2)

0.3

(1.5)

1.4

(7)

1.8

(9)

14.9

(74.5)

1.0

(5)

1.2

(6)

0.3

(1.5)

0.3

(1.6)

13.9

(69.5)

23 Official Secrets Act 0 3 0 0 0 0 0 0 0 0 0 0 0 0

24

Electricity Act

7.8

2

0

0

0

0

0.1

(0.03)

0

6.1

(1.56)

0

0

0

0.1

(0.03)

0

25

Wildlife Protection Act

0.1

3

0

0

0

0

0

0

0.1

(3)

0

0

0.1

(3)

0

0.1

(3)

26

Bonded Labor System

(Abolition) Act

0.1*

3

0

0

0

0

0

0

0

0

0.1

(3)

0

0

0

27 Environmental (Protection) Act 0 3 0 0 0 0 0 0 0 0 0 0 0 0

28

Air (Prevention & Control of

Pollution) Act, 1981

0.1*

3

0

0

0

0

0

0

0.1

(3)

0

0

0

0

0


29

Water (Prevention & Control of

Pollution) Act, 1974

0

3

0

0

0

0

0

0

0

0

0

0

0

0

30

National Security Act

1.2*

4

0

0

0

0

1.2

(4)

0

0

0

0

0

0

0

31

Unlawful Activities

(Prevention) Act

0.1

3

0

0

0

0

0

0

0

0.2

(6)

0

0

0

0

32

Young Persons (Harmful Pub.)

Act

0.1

3

0

0

0

0

0

0

0

0

0

0

0

0

33

Railway Property (Unlawful

Possession) Act

0

3

0

0

0

0

0

0

0

0

0

0

0

0

34

Prevention of Damage To

Public Property Act

0.4

3

0

0

1.3

(9.75)

0.4

(3)

0

0

1.5

(11.25

)

1.0

(7.5)

0

0.8

(6)

0

0

35

Transplantation of Human

Organs Act

0

4

0

0

0

0

0

0

0

0

0

0

0

0

36 Trade Marks Act 0.1* 2 0.1 0 0 0.1 0 0 0 0 0 0 0 0

(2) (2)

37

Prevention of Insults To

National Honor Act

0

3

0

0

0

0

0

0

0

0

0

0

0

0

38

State Emblem of India

(Prohibition of Improper Use)

Act, 2005

0

2

0

0

0

0

0

0

0

0

0

0

0

0

39

Lotteries (Regulation) Act

0.3

2

0

0

15.5

(103.3

3)

3.0

(20)

0

0

0

0

3.4

(22.67

)

0

0

0

40 Citizenship Act, 1955 0 3 0 0 0 0 0 0 0 0 0 0 0 0

41

Foreigners Act

0.2

3

0

0

0

0

0

0

0

0

0.1

(1.5)

0.1

(1.5)

0

0

42

Place of Worship (Spl

Provisions) Act

0

2

0

0

0

0

0

0

0

0

0

0

0

0

43

Religious Institution (Prevention

of Misuse) Act

0

2

0

0

0

0

0

0

0

0

0

0

0

0


44

Representation of the People

Act

0.1

3

0

0

0

0

0

0

0

0

0

0

0

0

45

Emigration Act

0.5*

3

0

0

0

0

0

0

0

0.8

(4.8)

0.5

(3)

0

0

0

46

Juvenile Justice (Care And

Protection of Children) Act

0.1*

3

0.2

(6)

0

0

0

0

0

5.3

(159)

0.4

(12)

0.5

(15)

0.1

(3)

0

0

47

Infant Milk Substitutes, Feeding

Bottles And Infant Foods

(Regulation of Production,

Supply and Distribution)

Amendment Act

0

3

0

0

0

0

0

0

0

0

0

0

0

0

48 Anti-Hijacking Act, 1982 0 4 0 0 0 0 0 0 0 0 0 0 0 0

49 Atomic Energy Act, 1962 0 4 0 0 0 0 0 0 0 0 0 0 0 0

50

Weapons of Mass Destruction

and their Delivery Systems

(Prohibition of Unlawful

0

5

0

0

0

0

0

0

0

0

0

0

0

0

Activities) Act

51 Safety of Civil Aviation Act 0 4 0 0 0 0 0 0 0 0 0 0 0 0

52

Safety of Maritime Navigation

& Fixed Platforms On

Continental Shelf Act

0

4

0

0

0

0

0

0

0

0

0

0

0

0

53

Manual Scavengers &

Construction of Dry Latrines

(Prohibition) Act

0

2

0

0

0

0

0

0

0

0

0

0

0

0

54

Pre-Natal Diagnostic

Techniques (Regulation &

Prevention of Misuse) Act

0

3

0

0

0

0

0

0

0

0

0

0

0

0

55

The Maritime Zones of India

(Regulation of fishing by

foreign vessels) Act, 1981

0

2

0

0

0

0

0

0

0

0

0

0

0

0

56

Other SLL Crimes

258.

9

2

32.1

(0.25)

1.3

(0.01)

111.9

(0.86)

843.9

(6.52)

2.7

(0.02)

3.4

(0.03)

43.9

(0.34)

1125.4

(8.69)

19.5

(0.15)

35.4

(0.27)

392.4

(3.03)

1.6

(0.01)

Total nRCC

(46.9)

(90.54

)

(197.7

6)

(129.5

1)

(83.39

)

(140.3

4)

(307.1

4)

(164.6

7)

(138.0

2)

(55.5

1)

(63.86

)

(136.4

)

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